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      1 /* Copyright 2016 The TensorFlow Authors. All Rights Reserved.
      2 
      3 Licensed under the Apache License, Version 2.0 (the "License");
      4 you may not use this file except in compliance with the License.
      5 You may obtain a copy of the License at
      6 
      7     http://www.apache.org/licenses/LICENSE-2.0
      8 
      9 Unless required by applicable law or agreed to in writing, software
     10 distributed under the License is distributed on an "AS IS" BASIS,
     11 WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
     12 See the License for the specific language governing permissions and
     13 limitations under the License.
     14 ==============================================================================*/
     15 
     16 #include "tensorflow/core/common_runtime/graph_optimizer.h"
     17 
     18 #include "tensorflow/core/common_runtime/constant_folding.h"
     19 #include "tensorflow/core/common_runtime/function.h"
     20 #include "tensorflow/core/common_runtime/optimization_registry.h"
     21 #include "tensorflow/core/graph/algorithm.h"
     22 #include "tensorflow/core/graph/node_builder.h"
     23 #include "tensorflow/core/graph/optimizer_cse.h"
     24 
     25 namespace tensorflow {
     26 namespace {
     27 
     28 // Replaces occurrences of parallel_concat with the implementation based on
     29 // unsafe ops. Sets removed_any to true if any parallel_concats were removed;
     30 // leaves it untouched otherwise.
     31 class ParallelConcatRemovePass : public GraphOptimizationPass {
     32  public:
     33   Status Run(const GraphOptimizationPassOptions& options) override {
     34     if (options.graph == nullptr) {
     35       // TODO(apassos) returning OK feels weird here as we can't do anything
     36       // without a graph, but some tests require this.
     37       return Status::OK();
     38     }
     39     Graph* g = options.graph->get();
     40     if (g == nullptr) {
     41       return errors::Internal(
     42           "Parallel concat removal should happen before partitioning and a "
     43           "graph should be available.");
     44     }
     45     gtl::InlinedVector<Node*, 2> matches;
     46     for (Node* n : g->op_nodes()) {
     47       if (n->type_string() == "ParallelConcat") {
     48         matches.push_back(n);
     49       }
     50     }
     51     for (Node* n : matches) {
     52       AttrSlice n_attrs = n->attrs();
     53       auto base_make_node = [n, g, &n_attrs](const string& op,
     54                                              const string& name) {
     55         NodeBuilder node_builder(name, op);
     56         node_builder.Device(n->requested_device());
     57         string colo;
     58         if (GetNodeAttr(n_attrs, "_class", &colo).ok()) {
     59           node_builder.Attr("_class", colo);
     60         }
     61         return node_builder;
     62       };
     63       auto make_node = [n, g, &n_attrs, &base_make_node](string op) {
     64         return base_make_node(
     65             op, g->NewName(strings::StrCat(n->name(), "/Internal")));
     66       };
     67       DataType dtype;
     68       TF_RETURN_IF_ERROR(GetNodeAttr(n_attrs, "T", &dtype));
     69       TensorShapeProto shape;
     70       TF_RETURN_IF_ERROR(GetNodeAttr(n_attrs, "shape", &shape));
     71 
     72       // Add the start node
     73       Node* start;
     74       TF_RETURN_IF_ERROR(make_node("_ParallelConcatStart")
     75                              .Attr("shape", shape)
     76                              .Attr("dtype", dtype)
     77                              .Finalize(g, &start));
     78 
     79       // Add all the inplace_updates.
     80       std::vector<Node*> control_nodes;
     81       int64 i = 0;
     82       for (const Edge* input_edge : n->in_edges()) {
     83         if (input_edge->IsControlEdge()) {
     84           g->AddControlEdge(input_edge->src(), start);
     85           continue;
     86         }
     87 
     88         Node* update;
     89         TF_RETURN_IF_ERROR(
     90             make_node("_ParallelConcatUpdate")
     91                 .Attr("loc", i)
     92                 .Input(start)
     93                 .Input(input_edge->src(), input_edge->src_output())
     94                 .Finalize(g, &update));
     95         control_nodes.push_back(update);
     96 
     97         ++i;
     98       }
     99 
    100       // Add the final identity.
    101       NodeBuilder identity_def = base_make_node("Identity", n->name());
    102       identity_def.Input(start, 0);
    103       for (Node* s : control_nodes) {
    104         identity_def.ControlInput(s);
    105       }
    106       Node* identity_node;
    107       TF_RETURN_IF_ERROR(identity_def.Finalize(g, &identity_node));
    108 
    109       // Remove the node and redirect edges.
    110       for (auto* e : n->out_edges()) {
    111         if (e->IsControlEdge()) {
    112           g->AddControlEdge(identity_node, e->dst());
    113         } else {
    114           g->AddEdge(identity_node, 0, e->dst(), e->dst_input());
    115         }
    116       }
    117       g->RemoveNode(n);
    118     }
    119     return Status::OK();
    120   }
    121 };
    122 REGISTER_OPTIMIZATION(OptimizationPassRegistry::PRE_PLACEMENT, 0,
    123                       ParallelConcatRemovePass);
    124 
    125 }  // namespace
    126 }  // namespace tensorflow
    127